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The Utilization of Soft Computing in Ordering Cycle Management
Šustrová, Tereza ; Fecenko, Josef (referee) ; Jurová, Marie (referee) ; Marček, Dušan (referee) ; Dostál, Petr (advisor)
This doctoral thesis deals with possibilities of using advanced methods of decision-making - Soft Computing, in company’s ordering cycle management. The main aim of the thesis is to propose an artificial neural network model with an optimal architecture for ordering cycle management within the supply chain management. The proposed model will be employed in an organization involved in retailing to ensure smooth material flow. A design and verification of artificial neural networks model for sales prediction is also part of this doctoral thesis as well as a comparison of results and usability with standard and commonly used statistical methods. Furthermore, the thesis deals with finding a suitable artificial neural network model with architecture capable of solving the lot-size problem according to specified inputs. Methods of statistical data processing, economical modelling and advanced decision-making (Soft Computing) were utilized during the model designing process.
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Fuzzy investment decision support for brownfield redevelopment
Brož, Zdeněk ; Čapek, Jan (referee) ; Dostál, Petr (referee) ; Fecenko, Josef (referee) ; Dohnal, Mirko (advisor)
Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.
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Information Systems Assessment Methodology
Novák, Lukáš ; Fecenko, Josef (referee) ; Koráb, Vojtěch (referee) ; Molnár, Zdeněk (referee) ; Koch, Miloš (advisor)
The doctoral dissertation thesis is focused on assessment of information systems and defines the main deficiencies in operation and management of information systems in relation to processes in the department of informatics with partial overlapping into the other parts of the company. The thesis further extends the current view of assessment of information systems in the company and, in accordance with the goal of the work, it defines its own methodology, which defines the specific assessment process and subdivides its contents into individual units. The proposed methodology provides an overview of the deficiencies and possible measures in operation and management of information systems. Qualitative verification of methodology in small, medium and large companies using case studies form a part of the thesis as well.
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Information Systems Assessment Methodology
Novák, Lukáš ; Fecenko, Josef (referee) ; Koráb, Vojtěch (referee) ; Molnár, Zdeněk (referee) ; Koch, Miloš (advisor)
The doctoral dissertation thesis is focused on assessment of information systems and defines the main deficiencies in operation and management of information systems in relation to processes in the department of informatics with partial overlapping into the other parts of the company. The thesis further extends the current view of assessment of information systems in the company and, in accordance with the goal of the work, it defines its own methodology, which defines the specific assessment process and subdivides its contents into individual units. The proposed methodology provides an overview of the deficiencies and possible measures in operation and management of information systems. Qualitative verification of methodology in small, medium and large companies using case studies form a part of the thesis as well.
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The Utilization of Soft Computing in Ordering Cycle Management
Šustrová, Tereza ; Fecenko, Josef (referee) ; Jurová, Marie (referee) ; Marček, Dušan (referee) ; Dostál, Petr (advisor)
This doctoral thesis deals with possibilities of using advanced methods of decision-making - Soft Computing, in company’s ordering cycle management. The main aim of the thesis is to propose an artificial neural network model with an optimal architecture for ordering cycle management within the supply chain management. The proposed model will be employed in an organization involved in retailing to ensure smooth material flow. A design and verification of artificial neural networks model for sales prediction is also part of this doctoral thesis as well as a comparison of results and usability with standard and commonly used statistical methods. Furthermore, the thesis deals with finding a suitable artificial neural network model with architecture capable of solving the lot-size problem according to specified inputs. Methods of statistical data processing, economical modelling and advanced decision-making (Soft Computing) were utilized during the model designing process.
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Fuzzy investment decision support for brownfield redevelopment
Brož, Zdeněk ; Čapek, Jan (referee) ; Dostál, Petr (referee) ; Fecenko, Josef (referee) ; Dohnal, Mirko (advisor)
Tato disertační práce se zaměřuje na problematiku investování a podporu rozhodování pomocí moderních metod. Zejména pokud jde o analýzu, hodnocení a výběr tzv. brownfieldů pro jejich redevelopment (revitalizaci). Cílem této práce je navrhnout univerzální metodu, která usnadní rozhodovací proces. Proces rozhodování je v praxi komplikován též velkým počet relevantních parametrů ovlivňujících konečné rozhodnutí. Navržená metoda je založena na využití fuzzy logiky, modelování, statistické analýzy, shlukové analýzy, teorie grafů a na sofistikovaných metodách sběru a zpracování informací. Nová metoda umožňuje zefektivnit proces analýzy a porovnávání alternativních investic a přesněji zpracovat velký objem informací. Ve výsledku tak bude zmenšen počet prvků množiny nejvhodnějších alternativních investic na základě hierarchie parametrů stanovených investorem.
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